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IoT and Edge Computing: Extracting Insights in Real-Time

IoT is Driving Real-Time Analysis at the Network’s Edge

For many IoT applications, it has become critical for data to be screened and analyzed where it is generated - from sensors in a car, surveillance cameras, drones, personal devices, robots, gateways, etc. – and even transformed there. The ability to deliver real-time analytics at the network’s edge can improve operational efficiencies, provide safer driving, create more secure environments, foresee upcoming maintenance, identify customer buying behaviors, and enable a world of opportunities.

Network latency is a challenge. It takes too long to store and forward data, whose value exists now. Edge storage manages data captures and provides the compute capabilities that aggregate and analyze that data in real time, to deliver immediate and actionable insights at the device level.

Up to $11.1T/Year

The IoT market will have a total potential economic impact of $3.9 trillion to $11.1 trillion a year by 20251

507.5ZB by 2020

By 2020, more than five million smart sensors and other IoT devices will be in use around the world, and will generate at least 507.5 zettabytes of data2

47B by 2021

It is estimated that there will be 47 billion connected devices by 20213

What makes real-time analytics at the edge become possible or even preferred, not just now but in years to come, is the possibility of conducting artificial intelligence and machine learning (ML). AI and ML are becoming increasingly more complex, versatile and sophisticated to enable real-time analysis at the edge, on the hub and, ultimately, in the cloud to get more value from all of the IoT data collected. Data can be sent to the cloud, where machine learning and AI can be trained to watch for patterns and gain insights from large data sets over time.

SOURCE: UNTAPPED DATA – GETTING MORE FROM IOT DATA AT THE EDGE AND IN THE CLOUD BY CHRISTOPHER BERGEY, WESTERN DIGITAL (WESTERN DIGITAL BLOG, 5/6/18)

THE VALUE OF EDGE ANALYSIS

Edge Analysis Delivers Real-Time Value

Artificial intelligence (AI), machine learning (ML), image, voice and gesture recognition, and other technologies deployed onto edge devices interact with captured data in real time to deliver valuable insights. The full digestion of analytics can be transferred to the cloud where it can be used to further train AI models for machine learning or archived for future use. The ability to access this information in real time, ultimately, creates a more efficient and effective business, operation, or environment, enabling greater opportunities for monetization of the IoT application.

ENABLING THE POWER AND POSSIBILITIES OF DATA AT THE EDGE

Western Digital Offers an Extensive Portfolio of Products from Devices to Systems and Platforms Designed to Enable the Power and Possibilities of Data Driven by IoT and Edge Computing

IoT Data Lake

IOT DATA LAKE

Effectively Managing Internet of Things Data

One of the biggest challenges that enterprises encounter when exploring how to improve their businesses using Internet of Things (IoT) data is the sheer volume created by sensors. This staggering amount of data impedes the ability to efficiently access, manipulate, and gain insights from the vast and diverse world of data collected.

Cloud object systems were designed to handle the enormous volume of IoT data and can help you aggregate, store, manage and protect data in a centralized hybrid cloud system, while providing the ability to collaborate and share that data across the ecosystem.

ActiveScale object storage systems were specifically designed to handle massive amounts of data, such as that generated by IoT. Our high-density, low-power footprint, extreme durability, and compelling economics, means you can keep more data online versus deciding what to delete or take offline.

Big Data and Analytics — A Data Lake Infrastructure for the Future

Building a petabyte-scale data lake with one of the lowest TCOs and without compromising performance, scalability, and reliability.

The Explosion of M2M Connected Devices

Advancements in connectivity and compute miniaturization have fueled an explosion of smart and connected sensors that are used to harvest the benefits of IoT in almost every industry- from ag-tech to medical. And with that number expected to increase to 3.3 billion by 2021, how those devices generate, handle, and communicate data will have a huge impact on many vital industries.

These connected M2M devices require storage in the devices, as well as in the gateways used as aggregation points, and in various points on the network. all the way up to the cloud.

Adaptive solutions designed to handle everything from small footprint storage for the application stack of smart sensor to an Edge gateway server, while also resistant to high temperatures and humidity. Western Digital offers a variety of storage solutions built to fit the evolving needs of the IoT market.

IoT and Edge Solutions — Connected M2M Devices

For more information regarding Connected M2M Devices, please talk to an expert or send a message using the links below.

Managing the Avalanche of Data in IIoT

A fully Industrial Internet of Things (IIoT) enabled factory uses the latest in sensors, automation, augmented reality (AR), and analytics to ensure the highest quality product. This produces an avalanche of data, and that data needs to be stored and analyzed. While there are different locations in which that can take place, the best place to do that is at the edge, in order to minimize latency and to maximize responsiveness.

That edge gateway forms a pipeline. Low bandwidth data from nearby sources is aggregated into a single stream, and this stream is then processed quickly to detect and respond to critical conditions. Not every bit of data fed into the edge node is returned to the central cloud, and even less critical data is passed on to the data center for further processing. In the IIoT, speed is imperative to make quick decisions and the edge is critical in how quickly data is captured, processed and analyzed.

Because the data processed by IIoT has a real financial impact on a business, the edge needs to have ultra-reliable storage in a diverse set of form factors that have the performance necessary to minimize latency and maximize responsiveness.

IoT and Edge — Industrial IoT

For more information regarding Industrial IoT, please talk to an expert or send a message using the links below.

IOT EXPERTS AGREE

In ABI Research’s view, one of the most significant trends in the Internet of Things (or the connected world—the Internet of Everything—as a whole) is the shifting balance between edge computing and cloud computing. The early days of the IoT and its conceptual precursor, M2M, have been characterized by the critical role of cloud platforms as application enablers. Intelligent systems have largely relied on the cloud level for their intelligence, and the actual devices of which they consist have been relatively unsophisticated. This old premise is currently being shaken up, as the computing capabilities on the edge level advance faster than those of the cloud level.

SOURCE: EDGE ANALYTICS IN IOT, ABI RESEARCH, 2015

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